Monitoring and early fault prediction of large electrical machines is important to maintain a sustainable and safe power system. With the ever-increasing computational power of modern processors, real-time simulation based monitoring of electrical machines is becoming a topic of interest. This work describes the development of a real-time digital twin (RTDT) of a wound rotor induction machine (WRIM) using a precomputed finite element model fed with online measurements. It computes accurate outputs in real-time of electromagnetic quantities otherwise difficult to measure such as local magnetic flux, current in bars and torque. In addition, it considers space harmonics, magnetic imbalance and fault conditions. The development process of the RTDT is described thoroughly and outputs are compared in real-time to measurements taken from the actual machine in rotation. Results show that they are accurate with harmonic content respected.
When facing severe weather events, a distribution system may suffer from the loss or failure of one or more of its components, the so-called N-K contingencies. Nevertheless, taking advantage of the system’s isolate switches and the increasing availability of distributed energy resources (DERs), a distribution system may be clustered into microgrids able to withstand such contingencies with minimal power interruption. In this perspective, this work proposes a novel bilevel optimization framework for planning microgrids in active distribution systems under a resilience-oriented perspective. For this, first, the outer level optimization features a multi-objective problem seeking to optimally allocate DERs and isolate switches in the distribution network while balancing the competing objectives of cost, resilience, and environmental impact. Next, the inner level handles the optimization problem pertaining to the optimal operation of the microgrids that can be created by harnessing local DERs and isolate switches allocated in the outer level. Further, given the proposed approach resilience-oriented focus, the developed framework employes deep learning models based on deep neural network (DNN) architectures trained using Bayesian Regularization Backpropagation (BRB) technique. This strategy allows for avoiding the modeling simplifications typically employed to alleviate the computational burden that can otherwise jeopardize planning solutions’ feasibility. Thus, enabling the accurate consideration of microgrids’ operational behavior, including hierarchal controls and the stochastic nature of loads, generation, and weather-induced line failures, especially critical aspects under resilience-oriented planning. Simulation case studies are developed to demonstrate the effectiveness of the developed planning framework.
23 June 2017 in IEEE Transactions on Energy Conversion
A high-order model is required for an accurate simulation of the synchronous alternator spatial harmonic content. However, some hydro-generators have fractional slot per pole per phase windings, and carrying transient simulations of these machines with finite-element software often leads to unacceptable computation time. This paper details a large alternator modeling method that provides an excellent compromise between accuracy and speed. It is a combination of magnetostatic finite element method and coupled circuits model. The paper details the construction of this model and explains the procedures to identify several model parameters from experimental data as the standstill frequency response and open and short circuit tests. The effectiveness of this modeling method is validated by the study of a large 109-MVA hydrogenerator having an instrumented rotor pole. We compare transient and steady-state simulation waveforms of the damper bar currents during sudden two- and three-phase short-circuit to the experimental measures.
In linear particle accelerators, klystrons operating in synchronized pulsed mode are used for RF power production and their power supply is provided by modulators that are high voltage and high power pulse generators. One solid state topology of klystron modulator is using a monolithic High Voltage pulse transformer. Future electron-positron linear colliders like the Compact Linear Collider (CLIC) will need a huge number of klystron modulators with tight dynamical specifications and high efficiency for minimizing their power consumption. With such new complex specifications, the feasibility of the modulator topology needs the development of an accurate methodology for the design of High Power & High Voltage Pulse Transformers. This paper presents the first development steps of an optimal design environment of these devices in terms of modeling & dimensioning tools and its applications.
Eccentricity faults are one of the main causes that significantly affect the performance of permanent magnet synchronous machines (PMSMs). Monitoring eccentricity in real time could prevent failures by adapting operation conditions and maintenance schedule when early signs of deterioration are detected. This article proposes making a circuit-type model of a permanent magnet machine with an easily configurable eccentricity for simulations and real-time analysis of signals under different operating conditions. The basis for the construction of the circuit model will be the simulation of the PMSM with 49 different coordinates of the rotor center, using the finite element analysis (FEA). The presence of eccentricity causes a variation in the inductances, the no-load flux and the expansion torque depending on the position of the rotor. The model proposes the use of bilinear interpolation (BI) to estimate the inductance matrix, the no-load flux vector captured by the stator winding and the cogging torque due to the presence of the magnets in the rotor, all of them for each rotor position. The validation is done by comparing the precision in the results of the machine’s self-inductances, the torque and the voltage waveform at the PMSM terminals and the static torque of the PMSM. The circuit model results are validated in two ways: (1) through experimental simulation, comparing the same results obtained using FEA and (2) through practical experimentation, producing a dynamic eccentricity in the machine of 0.3 mm. The results show that the proposed model is capable of accurately reproducing the behavior of the PMSM against eccentricity faults and presents computational time savings close to 99% compared to the response time obtained using FEA. This rapid PMSM model, parameterizable according to the degree of eccentricity, is the basis for the real-time simulation of the main machine waveforms, such as voltage, current and torque.
Hybrid electric aero-propulsion requires high power-density electric motors. The use of a constrained optimization method with the finite element analysis (FEA) is the best way to design these motors and to find the best solutions which maximize the power density. This makes it possible to take into account all the details of the geometry as well as the non-linear characteristics of magnetic materials, the conductive material and the current control strategy. Simulations were performed with a time stepping magnetodynamic solver while taking account the rotor movement and the stator winding was connected by an external electrical circuit. This study describes the magnetic FEA direct optimization approach for the design of Halbach array permanent magnet synchronous motors (PMSMs) and its advantages. An acceptable compromise between precision and computation time to estimate the electromagnetic torque, iron losses and eddy current losses was found. The finite element simulation was paired with analytical models to compute stress on the retaining sleeve, aerodynamic losses, and copper losses. This type of design procedure can be used to find the best machine configurations and establish design rules based on the specifications and materials selected. As an example, optimization results of PM motors minimizing total losses for a 150-kW application are presented for given speeds in the 2000 rpm to 50,000 rpm range. We compare different numbers of poles and power density between 5 kW/kg and 30 kW/kg. The choice of the number of poles is discussed in the function of the motor nominal speed and targeted power density as well as the compromise between iron losses and copper losses. In addition, the interest of having the current-control strategy as an optimization variable to generate a small amount of flux weakening is clearly shown.